Rough set

Rough set is a way of dealing with uncertainty. It's a way of understanding data that has some uncertainty—where you may not know everything about it. It can help you figure out what you do know, and what you don't know, about your data. To understand it more, let’s use an example. Imagine you have a group of animals - cows, horses, sheep, and pigs. And for each animal, you know some facts about them: how many legs they have, how they look, or what noise they make. But you don’t know everything about each animal. You don’t know their colours, or if they have horns, or what they weigh.

Rough set helps us by using the information we do have to make some guesses about the things we don't know. It looks at the animals we know and the information we have and tries to figure out the things we don’t know. So using Rough Set, we can learn that all the animals have four legs, they all make a noise, and they all have fur. We can also use it to make an educated guess about which animals might have horns, or be bigger than the others.

Basically, Rough Set is a way to use what we do know to help us work out what we don’t know.